If it is helpful, I would like to contribute 
Just like world university rankings, there are lots of different versions and ranking methods. However, the ranking from well-known websites or media would make it easy for general users to accept.
This comment is just from the website of RedMonk, and the full comments are as follows.
Julia (3) : A week or so ago, we received the following inquiry from a large vendor: âwhat are your thoughts on Julia â is it going to remain a niche language or grow or die?â The inquiry was interesting, both because of where it came from and because we havenât had anybody ask about Julia in some time. While itâs been written up here before, it has tended to move very slowly and thus hasnât attracted much attention. But the inquiry was well timed, because according to our rankings Julia is making slow but steady progress. This quarter Julia jumped three spots to 36, which is its fourth consecutive quarter of growth (36, 39, 40, 52). Itâs certainly not on a Kotlin or Swift path, and the esoteric nature of the language may yet relegate it to niche status, but its steady performance has put it back on the map as one to watch. (RedMonk, August 10, 2018)
For the people who never use Julia may consider Julia as a scientific computing language like Fortran or Matlab, although Julia can do much more. Maybe some famous projects would make more people know the features of Julia, just like Atom and Visual Studio Code let people know that Javascript is also good at Desktop GUI developing.
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There is also this rank: PYPL PopularitY of Programming Language index (PopularitY of Programming Language). Julia is number 21 there and is going up.
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Thatâs an interesting ranking. The results feel a lot less noisyâwhich makes sense since google searches are a really statistically reliable data source. But the results seem heavily biased towards languages that people are learning rather than those that people already know and are using on a daily basis. Note the complete absence of C and C++ from the list!
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It is #6.
That said, if one is learning C/C++ from a tutorial, something is horribly wrong. At least a book would be necessary; each is fairly complex and does not decompose well into a minimum viable subset, especially C++. Same goes for Haskell.
Could also be an indicator of quality of syntax and/or documentation quality - for me personally, using R I reckon I average out at 2-3 google queries per finished line of code, whereas with Julia that number is much closer to zero (numbers might be exaggerated for effect).
Along those lines itâd be interesting to see the extent to which the recent uptick in interest was driven by the query julia variable not defined errorâŚ
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Oh man, I somehow totally missed that! Maybe because I was expecting them as separate entries, not a single entry. Still, sixth is unusually low as a ranking for C or C++ let alone the two together, so I think it does show that there is a bias as compared to other (also biases but in different ways) rankings.
Redmonk January 2019 - ( posted by: March 20, 2019 )
" Julia : For a language that isnât even in the Top 30, Julia continues to attract questions about its performance and future. Its growth has been more tortoise than hare, but itâs up another two spots to place #34. While there is no technical basis for comparison, it is worth noting that three years ago in our Q1 rankings TypeScript made a similar modest jump from #33 to #31. That is not to say that Julia is destined to follow in TypeScriptâs footprints, of course, but rather to serve as a reminder that while itâs uncommon languages can transition quickly from periods of slow, barely measurable growth to high, sustained growth quarter after quarter."
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In the 2019 IEEE Spectrum language rankings youâll find that Julia is ranked as the number 2 Enterprise language for either âGithubâ metrics. Of course this is only fun numerology 
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This means that Julia users are only programming while other language users are talking about their language on other platforms!
Even enabling other language types doesnât affect the ranking:
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Does it, really? I am not sure about this.
I think that at this point Julia is a very solid language for the whole spectrum of scientific programming, from fast prototyping to delivering robust and well-designed packages that can be combined to solve problems.
But scientific programming is still a small, very specialized field of programming, with highly trained domain experts mostly working in research, or knowledge-intensive private sector jobs. So we are unlikely to win any generic popularity contests, and this is perfectly fine. Fiddling with the objective function to make Julia look âmore popularâ is not necessary.
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It seems like a reasonable statement, especially since Julia projects are more likely to be distributed on github than Matlab or Mathematica code, languages that are more talked about with less code repositories. With the Julia language, coders can get started more easily with code repositories and having working code with less questions perhaps. In the closed source ecosystems, there is naturally less code out in the open.
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That is not necessarily true: there is more Matlab code out there than Julia. Most of it is floating around in files, without version control (itâs great fun where people make small modifications without documenting why, and you end up with 17 seemingly near-equivalent but quite different versions of the same script). But a lot of it is now on Github, Gitlab, BitBucket, etc.
But Matlab has been around for 35 years, so this is not surprising.
I think that instead of figuring out ways to make Julia look popular in these surveys or rationalize why it isnât, we should just accept the fact Julia is a young language, built for a specific community. This means even if we tentatively accept âpopularityâ as a proxy for quality, general popularity contests are not the right way to measure this.
Most importantly, while some people follow the crowd, but there are lots of programmers who are smart enough to make their own decisions about a language. They will evaluate Julia and judge it on its merits, and hopefully will find it to be a good match for their needs and join the community. I think we are seeing this happening every day here.
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While popularity is not a good standard for measuring quality, it specifies the language that you should program when you want to work in groups or for a company as a job.
So we should accept that popularity is very important and we should improve it.
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And we will, by just doing what we have been doing, passionately using and developing high quality Julia software. The language is already trending upwards so it seems to be working just fine.
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We just published a blog on TIOBE ranking that might be interesting for this discussion. We basically find that TIOBE uses the search term +âjulia programmingâ, and if you use +âjulia languageâ, we end up about 10 spots higher (applying the same method to all the other languages too). This is also closer to what IEEE Spectrum ranking finds.
We hope our blog post is useful input to TIOBE on methodology, since they do invite such input.
-viral
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What happens if you do the same analysis searching for
(â_ languageâ OR â_ programmingâ), where _ is the name?
If I understand correctly, that is exactly what they did:
We selected the TIOBE top 40 languages and recalculated the rankings using this combined query (
+"X language" OR +"X programming").
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Yes, thatâs what the analysis was.